sepFilter2D Opencv unexpected results - c++

Question

I'm trying to apply 8X8 separable mean filter on top of an image
The filter is 2D separable.
I'm converting the following code from Matlab,
Kernel = ones(n);
% for conv 2 without zeropadding
LimgLarge = padarray(Limg,[n n],'circular');
LimgKer = conv2(LimgLarge,Kernel,'same')/(n^2);
LKerCorr = LimgKer(n+1:end-n,n+1:end-n);
1st I pad the image with the filter size, than correlate 2d, and finally crop the image region.
Now, I'm trying to implement the same thing in C++ using opencv
I have loaded the image, than called the following commands:
m_kernelSize = 8;
m_kernelX = Mat::ones(m_kernelSize,1,CV_32FC1);
m_kernelX = m_kernelX / m_kernelSize;
m_kernelY = Mat::ones(1,m_kernelSize,CV_32FC1);
m_kernelY = m_kernelY / m_kernelSize;
sepFilter2D(m_logImage,m_filteredImage,m_logImage.depth(),m_kernelX,m_kernelY,Point(-1,-1),0,BORDER_REPLICATE);
I expected to receive the same results, but I'm still getting totally different results from Matlab.
I'd rather not to pad the image , do the correlation and finally crop the image again, I expected the same results using BORDER_REPLICATE argument.
Incidentally, I'm aware of copyMakeBorder function, but rather not use it, because sepFilter2D handles the regions by itself.

Answer 1

Since you said you are only loading the image before the code snippet you showed, I can see two potential flaws.
First, if you do nothing between the loading of the source image and your code snippet, then your source image would be an 8-bit image and, since you set the function argument ddepth to m_logImage.depth(), you are also requesting a 8-bit destination image.
However, after reading the documentation of sepFilter2D, I am not sure that this is a valid combination of src.depth() and ddepth.
Can you try using the following line:
sepFilter2D(m_logImage,m_filteredImage,CV_32F,m_kernelX,m_kernelY,Point(-1,-1),0,BORDER_REPLICATE);
Second, check that you loaded your source image using the flag CV_LOAD_IMAGE_GRAYSCALE, so that it only has one channel and not three.

Answer 2

I followed Matlab line by line, The mistake was somewhere else.
Anyways , The following two methods return the same results
Using a 8X8 filter
// Big filter mode - now used only for debug mode
m_kernel = Mat::ones(m_kernelSize,m_kernelSize,type);
cv::Mat LimgLarge(m_logImage.rows + m_kernelSize*2, m_logImage.cols + m_kernelSize*2,m_logImage.depth());
cv::copyMakeBorder(m_logImage, LimgLarge, m_kernelSize, m_kernelSize,
m_kernelSize, m_kernelSize, BORDER_REPLICATE);
// Big filter
filter2D(LimgLarge,m_filteredImage,LimgLarge.depth(),m_kernel,Point(-1,-1),0,BORDER_CONSTANT );
m_filteredImage = m_filteredImage / (m_kernelSize*m_kernelSize);
cv::Rect roi(cv::Point(0+m_kernelSize,0+m_kernelSize),cv::Point(m_filteredImage.cols-m_kernelSize, m_filteredImage.rows-m_kernelSize));
cv::Mat croppedImage = m_filteredImage(roi);
m_diffImage = m_logImage - croppedImage;
Second method, using separable 8x8 filter
sepFilter2D(m_logImage,m_filteredImage,m_logImage.depth(),m_kernelX,m_kernelY,Point(-1,-1),0,BORDER_REPLICATE);
m_filteredImage = m_filteredImage / (m_kernelSize*m_kernelSize);